A discrete differential evolution for fuel loading optimization of the DNRR research reactor and comparison with genetic algorithm

Abstract

Abstract A discrete differential evolution (DE) method has been applied to the problem of fuel loading pattern optimization of the Dalat Nuclear Research Reactor (DNRR). A classic strategy DE/rand/l/bin was chosen for the mutation of the DE method. Numerical calculations have been performed based on the core configuration of 100 highly enriched uranium (HEU) fuel bundles with various burnup levels. Comparison of the performance between the DE method and a genetic algorithm (GA) was also carried out. The optimal LPs obtained from the two methods are significantly better than the reference core. DE is more advantageous in exploring search space and approaching a global optimum than GA.